Frequency-Adaptive Multi-Resonant LQG State-Feedback Current Controller for LCL-Filtered VSCs under Distorted Grid Voltages

This paper combines the well-known linear quadratic Gaussian (LQG) control and frequency-adaptive resonators and presents a frequency-adaptive multiresonant LQG state-feedback current controller for LCLfiltered voltage-source converters connected to a distorted grid. The paper also provides a design guideline and procedure based on robust control criteria which, in combination with the linear quadratic regulator (LQR) technique, offers flexibility in the control structure and automatizes the design of the controller. The frequencyadaptive resonators, based on second-order IIR resonators and on an on-line tuning algorithm, and the robustness criteria considered for the design process offer robustness in the face of grid voltage disturbances.The controller is evaluated and validated in a 9-kVA VSC setup configured as a rectifier.This work was supported in part by the Government of Spain through the Ministerio de Economía, Industria y Competitividad and Agencia Estatal de Investigación under Grants ENE2014-57760-C2-2-R, RTC-2015-3803-3, DPI2017-88505-C2-2-R and DPI2017-92258-EXP

Adaptive Reference Trajectory for Power Quality Enhancement in Three-Phase Four-Wire Standalone Power Supply Systems with Nonlinear and Unbalanced Loads

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State feedback control for a PM hub motor based on gray Wolf optimization algorithm

© 1986-2012 IEEE. This paper presents an optimal control strategy for a permanent-magnet synchronous hub motor (PMSHM) drive using the state feedback control method plus the gray wolf optimization (GWO) algorithm. First, the linearized PMSHM mathematical model is obtained by voltage feedforward compensation. Second, to acquire satisfactory dynamics of speed response and zero d-axis current, the discretized state-space model of the PMSHM is augmented with the integral of rotor speed error and integral of d-axis current error. Then, the GWO algorithm is employed to acquire the weighting matrices Q and R in linear quadratic regulator optimization process. Moreover, a penalty term is introduced to the fitness index to suppress overshoots effectively. Finally, comparisons among the GWO-based state feedback controller (SFC) with and without the penalty term, the conventional SFC, and the genetic algorithm enhanced proportional-integral controllers are conducted in both simulations and experiments. The comparison results show the superiority of the proposed SFC with the penalty term in fast response

Off-line optimization based active control of torsional oscillation for electric vehicle drivetrain

© 2017 by the authors. As there is no clutch or hydraulic torque converter in electric vehicles to buffer and absorb torsional vibrations. Oscillation will occur in electric vehicle drivetrains when drivers tip in/out or are shifting. In order to improve vehicle response to transients, reduce vehicle jerk and reduce wear of drivetrain parts, torque step changes should be avoided. This article mainly focuses on drivetrain oscillations caused by torque interruption for shifting in a Motor-Transmission Integrated System. It takes advantage of the motor responsiveness, an optimal active control method is presented to reduce oscillations by adjusting motor torque output dynamically. A rear-wheel-drive electric vehicle with a two gear automated manual transmission is considered to set up dynamic differential equations based on Newton's law of motion. By linearization of the affine system, a joint genetic algorithm and linear quadratic regulator method is applied to calculate the real optimal motor torque. In order to improve immediacy of the control system, time consuming optimization process of parameters is completed off-line. The active control system is tested in AMEsim® and limitation of motor external characteristics are considered. The results demonstrate that, compared with the open-loop system, the proposed algorithm can reduce motion oscillation to a satisfied extent when unloading torque for shifting